This component connects to a Elasticsearch server to retrieve data and load it into a table. This stages the data, so the table is reloaded each time. You may then use transformations to enrich and manage the data in permanent tables.
The component offers both a Basic and Advanced mode (see below) for generating the Elasticsearch query.
Warning: This component is destructive as it truncates or recreates its target table on each run. Do not modify the target table structure manually.
|Name||Text||The descriptive name for the component.|
Basic - This mode will build a Elasticsearch Query for you using settings from Data Source, Data Selection
and Data Source Filter parameters. In most cases, this will be sufficient.
Advanced - This mode will require you to write an SQL-like query which is translated into one or more Elasticsearch queries.
|Authentication Method||Select||Choose a method to authenticate your connection to the Elasticsearch server. Component properties will change to reflect this choice. Available choices are User/Password, PKI and None.
Note: When using 'None', for an instance on an AWS Elasticsearch server, the Matillion ETL instance should be on the same VPC.
|Server||Text||The server IP or DNS address of the Elasticsearch server endpoint.|
|Port||Text||Use to provide a port number. The default port for Elasticsearch listening for HTTP traffic is 9200.|
|SSLClientCert||Text||When using a PFXFile, this must be the name of that file. When using PFXBlob, this must be the contents of your PFXBlob file in Base64 format (binary file contents). (Available if Authentication Method is PKI)|
|SSLClientCertType||Text||All supported PKI forms are valid but we highly recommend using 'PFXBLOB' for the best compatibility with Matillion ETL. (Available if Authentication Method is PKI)|
|SSLClientCertSubject||Text||The email address of this client. Must be in the format 'EMAILADDRESS=<email@example.com>'. e.g.
(Available if Authentication Method is PKI)
|SSLClientCertPassword||Text||The password for this client. (Available if Authentication Method is PKI)|
|Username||Text||A valid Elasticsearch Username to use for authentication. (Available when Authentication Method is 'User/Password')|
|Password||Text||A valid password for the Username above. (Available when Authentication Method is 'User/Password')|
|Data Source||Choice||The name of a Elasticsearch collection. Collections are analogous to Tables in other databases.|
|Data Selection||Choice||Select one or more columns to return from the query. Columns are determined by scanning the first few documents and looking for fields that appear in each document.|
|Data Source Filter||Input Column||The available input columns vary depending upon the Data Source and are determined automatically by scanning a number of documents.|
Is - Compares the column to the value using the comparator.
Not - Reverses the effect of the comparison, so "equals" becomes "not equals", "less than" becomes "greater than or equal to", etc.
|Comparator||Choose a method of comparing the column to the value. Possible comparators include: 'Equal To', 'Greater than', 'Less than', 'Greater than or equal to', 'Less than or equal to', 'Like', 'Null'.
'Equal To' can match exact strings and numeric values while other comparators such as 'Greater than' will work only with numerics. The 'Like' operator allows the wildcard character (%) to be used at the start and end of a string value to match a column. The Null operator matches only Null values, ignoring whatever the value is set to.
Not all data sources support all comparators, thus it is likely only a subset of the above comparators will be available to choose from.
|Value||The value to be compared.|
|Combine Filters||Choice||And - Multiple filters must ALL be true for a row to be returned.
Or - Any one of the filters must be true for a row to be returned.
|Limit||Number||Provides an upper limit on the number of rows retrieved from the Elasticsearch server. Blank means fetch all records.|
|SQL Query||Text||This is an SQL-like SELECT query. Treat collections as tables names, and fields as columns. (Property only available in 'Advanced' Mode)|
|Connection Options||Parameter||A JDBC parameter supported by the Database Driver. The available parameters
are determined automatically from the driver, and may change from
version to version.
They are usually not required as sensible defaults are assumed.
|Value||A value for the given Parameter. The parameters and allowed values for the Elasticsearch provider are
|Storage Account||Select||(Azure Only) Select a Storage Account with your desired Blob Container to be used for staging the data.|
|Blob Container||Select||(Azure Only) Select a Blob Container to be used for staging the data.|
(AWS Only) Snowflake Managed: Allow Matillion ETL to create and use a temporary internal stage on Snowflake for staging the data. This stage, along with the staged data, will cease to exist after loading is complete.
Existing Amazon S3 Location: Selecting this will avail the user of properties to specify a custom staging area on S3.
|S3 Staging Area||Text||(AWS Only) The name of an S3 bucket for temporary storage. Ensure
your access credentials have S3 access and permission to write
to the bucket. See this document for
details on setting up access. The temporary objects created in this bucket will be removed again after the load completes, they are not kept.
This property is available when using an Existing Amazon S3 Location for Staging.
|Warehouse||Select||Choose a Snowflake warehouse that will run the load.|
|Database||Select||Choose a database to create the new table in.|
|Type||Select||Choose between using a standard table or an external table.
Standard: The data will be staged on an S3 bucket before being loaded into a table.
External: The data will be put into an S3 Bucket and referenced by an external table.
|Schema||Select||Select the table schema. The special value, [Environment Default] will use the schema defined in the environment. For more information on using multiple schemas, see this article.
Note: An external schema is required if the 'Type' property is set to 'External'.
|Target Table||Text||Provide a new table name.
Warning: This table will be recreated and will drop any existing table of the same name.
|Location||Text/Select||When using an 'External' type table, Provide an S3 Bucket path that will be used to store the data. Once on an S3 bucket, the data can be referenced by the external table.|
|Table Distribution Style||Select||
Even - the default option, distribute rows around the Redshift Cluster evenly.
All - copy rows to all nodes in the Redshift Cluster.
Key - distribute rows around the Redshift cluster according to the value of a key column.
Table-distribution is critical to good performance - see the Amazon Redshift documentation for more information.
|Table Distribution Key||Select||This is only displayed if the Table Distribution Style is set to Key. It is the column used to determine which cluster node the row is stored on.|
|Table Sort Key||Select||This is optional, and specifies the columns from the input that should be
set as the table's sort-key.
Sort-keys are critical to good performance - see the Amazon Redshift documentation for more information.
|Sort Key Options||Select||Decide whether the sort key is of a compound or interleaved variety - see the Amazon Redshift documentation for more information.|
|Project||Text||The target BigQuery project to load data into.|
|Dataset||Text||The target BigQuery dataset to load data into.|
|Cloud Storage Staging Area||Text||The URL and path of the target Google Storage bucket to be used for staging the queried data.|
|Encryption||Select||(AWS Only) Decide on how the files are encrypted inside the S3 Bucket.This property is available when using an Existing Amazon S3 Location for Staging.
None: No encryption.
SSE KMS: Encrypt the data according to a key stored on KMS.
SSE S3: Encrypt the data according to a key stored on an S3 bucket
|KMS Key ID||Select||(AWS Only) The ID of the KMS encryption key you have chosen to use in the 'Encryption' property.|
|Load Options||Multiple Selection||
Comp Update: Apply automatic compression to the target table (if ON). Default is ON.
Stat Update: Automatically update statistics when filling a table (if ON). Default is ON. In this case, it is updating the statistics of the target table.
Clean S3 Objects: Automatically remove UUID-based objects on the S3 Bucket (if ON). Default is ON. Effectively decides whether to keep the staged data in the S3 Bucket or not.
String Null is Null: Converts any strings equal to "null" into a null value. This is case sensitive and only works with entirely lower-case strings. Default is ON.
Recreate Target Table:Choose whether the component recreates its target table before the data load. If OFF, the existing table will be used. Default is ON.
|Load Options||Multiple Select||Clean Cloud Storage Files: (If On) Destroy staged files on Cloud Storage after loading data. Default is On.
Cloud Storage File Prefix: Give staged file names a prefix of your choice. Default is empty (no prefix).
|Auto Debug||Select||Choose whether to automatically log debug information about your load. These logs can be found in the Task History and should be included in support requests concerning the component. Turning this on will override any debugging Connection Options.|
|Debug Level||Select||The level of verbosity with which your debug information is logged. Levels above 1 can log huge amounts of data and result in slower execution.
1: Will log the query, the number of rows returned by it, the start of execution and the time taken, and any errors.
2: Will log everything included in Level 1, cache queries, and additional information about the request, if applicable.
3: Will additionally log the body of the request and the response.
4: Will additionally log transport-level communication with the data source. This includes SSL negotiation.
5: Will additionally log communication with the data source and additional details that may be helpful in troubleshooting problems. This includes interface commands.
This component makes the following values available to export into variables:
|Time Taken To Stage||The amount of time (in seconds) taken to fetch the data from the data source and upload it to storage.|
|Time Taken To Load||The amount of time (in seconds) taken for the COPY statement to load the data into the target table from the staging area.|
Connect to the Elasticsearch Server and issue the one or more queries. Stream the results into objects into a storage area, recreate or truncate the target table as necessary and then use a COPY command to load the stored objects into the table. Finally, clean up the temporary stored objects.
In this example we want to load user data from an Elasticsearch server. The Orchestration job to load the data is shown below.
Our Orchestration job uses the Elasticsearch Query to load in data from the Elasticsearch server. We have authenticated our connection to the server using PKI with details entered into the 'SSLClient' properties on the component. When run, this component loads the data into the target table 'doc_tbl' which can be sampled using a Table Input component in a Transformation job. The sample is shown below.
However, we now decide we want to refine this data to include only active users. We could have done this using the 'Data Filter' property on the Elasticsearch Query component before the load. Since the load is already completed, we decide instead to use a Filter component in a Transformation job, shown below.
The filter is set up to include only examples where values in the 'isactive' column are 'true'.
Since our Transformation job includes the Table Update component, this data will be written to doc_tbl, overwriting our earlier data. Now we can sample the data once more to show our final, refined data. Notice that in the filtered data, we now only have rows where 'isactive' is 'true'.